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ADVANCED TOPICS IN STATISTICS A

STA5ATA

2020

Credit points: 15

Subject outline

This subject enables 5th year students to enrol in subjects offered through the Key Centre of Statistical Science (KCSS), AMSI summer school or through the Department of Mathematics and Statistics Access Grid Room. Subject syllabus is dependent on the subject chosen and students are advised to refer to the departmental website or the Department of Mathematics and Statistics Master of Data Science Coordinator prior to enrolment for more details. Enrolment into this subject must be approved by the Department of Mathematics and Statistics Master of Data Science Coordinator.

School: Engineering and Mathematical Sciences (Pre 2022)

Credit points: 15

Subject Co-ordinator: Andriy Olenko

Available to Study Abroad/Exchange Students: Yes

Subject year level: Year Level 5 - Masters

Available as Elective: No

Learning Activities: N/A

Capstone subject: No

Subject particulars

Subject rules

Prerequisites: Only by approval of the Master of Data Science coordinator

Co-requisites: N/A

Incompatible subjects: STA4ATA

Equivalent subjects: N/A

Quota Management Strategy: N/A

Quota-conditions or rules: N/A

Special conditions: N/A

Minimum credit point requirement: N/A

Assumed knowledge: N/A

Career Ready

Career-focused: No

Work-based learning: No

Self sourced or Uni sourced: N/A

Entire subject or partial subject: N/A

Total hours/days required: N/A

Location of WBL activity (region): N/A

WBL addtional requirements: N/A

Graduate capabilities & intended learning outcomes

Graduate Capabilities

Intended Learning Outcomes

01. Demonstrate specialised theoretical and technical skills in a specified statistics topic.
02. Use specialised cognitive and technical skills to critically analyse, reflect on and synthesise complex information, problems, concepts and theories relevant to the topic.
03. Apply established theories relevant to the topic.
04. Use advanced communication skills to transmit knowledge and ideas of statistics to others.
05. Demonstrate autonomy, expert judgement, adaptability and responsibility as a statistician.

Melbourne (Bundoora), 2020, Semester 1, Day

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Subject Instance Co-ordinator: Andriy Olenko

Class requirements

LectureWeek: 10 - 22
Two 1.00 hour lecture per week on weekdays during the day from week 10 to week 22 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

This is dependent on the subject.

N/AN/AN/ANo100SILO1, SILO2, SILO3, SILO4, SILO5

Melbourne (Bundoora), 2020, Semester 2, Day

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Subject Instance Co-ordinator: Andriy Olenko

Class requirements

LectureWeek: 31 - 43
Two 1.00 hour lecture per week on weekdays during the day from week 31 to week 43 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

This is dependent on the subject.

N/AN/AN/ANo100SILO1, SILO2, SILO3, SILO4, SILO5

Melbourne (Bundoora), 2020, Summer 2 , Day

Overview

Online enrolment: Yes

Maximum enrolment size: N/A

Subject Instance Co-ordinator: Andriy Olenko

Class requirements

LectureWeek: 2 - 7
Six 1.00 hour lecture per week on weekdays during the day from week 2 to week 7 and delivered via face-to-face.

Assessments

Assessment elementCommentsCategoryContributionHurdle%ILO*

This is dependent on the subject.

N/AN/AN/ANo100SILO1, SILO2, SILO3, SILO4, SILO5